High-performance sensorless vector control of induction motor drives using artificial intelligent technique

This paper presents a sensorless speed observer method of an induction motor using an artificial intelligent technique in field-oriented control system. Speed and rotor flux are estimated from only measurable variables, the stator voltages and currents. The proposed estimation algorithm uses a deterministic state observer combined with an intelligent adaptive mechanism based on fuzzy logic, and using a knowledge base on human expertise. The introducing of fuzzy logic is applied to achieve high-performance, a low sensibility to parameter variations and external influences. The developed algorithm is robust and efficient, it also assures precise speed estimation, a good trajectory tracking with the different prescribed dynamics. In order to verify its performances test the behavior of the control algorithm, numerical simulations are achieved. The performances of the induction motor drive have been analyzed under steady state and transient conditions. The simulation results have shown a good estimate speed and flux and an excellent tracking performance of the proposed control system, and have demonstrated convincingly the usefulness of adaptive observer based on fuzzy logic in variable speed drives with high performance.